The overall goal of our proposed research is to develop a new lab-on-chip platform and a methodology to precisely determine molecular concentration by counting individual molecules and to implement this technique for the early detection of cancer. Unlike the conventional indirect sensing methods that require a conversion from output signals to molecular concentration, the proposed platform will directly measure molecular concentration and is thus expected to provide more accurate and reproducible concentration measurements. Currently, multiple serum-based breast cancer biomarkers such as CA15-3, BR27.29 (CA27.29), carcinoembryonic antigen, tissue polypeptide antigen, and HER2 (extra cellular domain) are being investigated as indicators of early-stage breast cancer. However, because of a lack of sensitivity and specificity-deficiencies caused by existing sensors'inability to accurately detect biomarker concentration-none of these biomarkers has been of value for detecting early-stage breast cancer. Thus, improving sensor accuracy should greatly improve the early detection of breast cancer. In this application, two specific aims are associated with proof-of-concept experiments. The first is to elicit and detect known concentrations of molecules by use of a proposed platform to optimize the processes and investigate the detection limit. The second is to determine the concentrations of biomarkers that are directly obtained from cultured cancer cells. PUBLIC HEALTH RELEVANCE: The overall goal of this proposed research is to develop nanochannel based plat-form that can identify specific molecules and count their concentrations. Because of the single-molecule accuracy, our proposed technique will be efficient and precise to determine the molecular concentration. Thus, it is expected to determine accurately the biomarker concentration that is highly demanded in the early detection of cancer. So far, we have completed the fabrication of nanochannels and obtained preliminary data for the determination of quantum dots concentrations. We are submitting this application for the R21 award category.